{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/9"},{"label":"Visualization","url":"https://skillfed.io/packages/category/scientific-engineering-visualization"},{"label":"Bio-Informatics","url":"https://skillfed.io/packages/category/scientific-engineering-bio-informatics"}],"enrichment":{"capability":"MultiQC scans bioinformatics analysis directories and generates a single interactive HTML report summarizing results across many samples and tools.","skillfed_tags":["bioinformatics","quality-control","reporting"],"use_cases":["Generate QC reports after running FastQC on hundreds of sequencing samples in a single command","Aggregate alignment statistics from multiple STAR or Bowtie2 runs into one comparative report","Create summary dashboards for variant calling pipelines combining results from multiple tools","Parse custom bioinformatics script output and include it in standardized reports via Custom Content","Monitor batch processing quality across different sequencing runs or experimental conditions","Export aggregated statistics in YAML or JSON format for downstream analysis or archival"],"what_it_does":"MultiQC is a command-line tool that aggregates bioinformatics analysis results from many samples into a single interactive report. It works by scanning specified directories for recognized log files from common bioinformatics tools (FastQC, Bowtie, STAR, and many others), parsing them, and generating an HTML report with interactive plots and summary statistics. The tool also produces tab-delimited data files for further inspection.\n\nThe package is designed for routine quality control in sequencing pipelines, allowing researchers to assess results across large sample batches at a glance. It supports custom content via configuration, has an extensible module system, and runs on Unix-like systems and macOS. With 26 runtime dependencies including plotly for visualization, numpy for data handling, and pydantic for validation, it provides a complete reporting pipeline for bioinformatics workflows.","worth_installing":"Yes. MultiQC is actively maintained, has low install friction, and solves a concrete problem for bioinformatics workflows. The GPLv3 license is standard in research contexts. The 26 dependencies are substantial but well-established (plotly, numpy, pydantic, polars). Install it if you regularly analyze multiple bioinformatics samples and need unified QC reporting; skip it if you work with single-sample analyses or already have a custom reporting pipeline."},"id":"multiqc","links":{"html":"https://skillfed.io/packages/multiqc","md":"https://skillfed.io/packages/multiqc.md","pypi":"https://pypi.org/project/multiqc/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-05-13","license_spdx":null,"license_treatment":"copyleft","name":"multiqc","python_support":"supports_current","summary":"Create aggregate bioinformatics analysis reports across many samples and tools"},"popularity":{"monthly_downloads":83223,"position":14091,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.35"}